The goal of the research is to combine the advantages of problem (patient) based learning with the immediate availability of a reliable source of information for the purpose of providing interesting and challenging computer-aided instruction to medical students in the disciplines of infectious diseases and microbiology. The primary hypothesis to be tested is that this end can be achieved by combining a Bayesian network with a database. The progress of the student towards a diagnosis will be tracked in the Bayesian network. The database will contain the knowledge that the student should assimilate in the subject area represented by the stimulated patient When the student requires information about a disease, concept, or test result, that information would be imported from the database and presented. During the course of the patient work-up, the student could learn from the Bayesian network the probabilities of the most likely diagnoses given the information available at that point and receive an explanation in plain language. Thus, the student would have everything available in a self-contained system to work through a thought-provoking patient problem and learn the associated subject matter. Furthermore, the individual student's path through the problem and learning may be individualized depending on the quantity of prior knowledge of the subject area and the student's choices as to sequential actions and diagnoses.